AFOSR/NSF Co-Sponsored Workshop on

Dynamic Data Driven Applications Systems (DDDAS) - Info-Symbiotic Systems

Arlington Hilton, Arlington, VA

August 30-31, 2010

Workshop Report

• 2010 DDDAS-IS Final Report

Previous Reports

• 2006 DDDAS Report and Executive Summary
• 2000 DDDAS Report
• 2006 SBES Report

Objectives

The Dynamic Data Driven Applications Systems (DDDAS) – Info-Symbiotic Systems workshop provides a forum for creating concerted support for a comprehensive set of activities enabling new capabilities engendered through the DDDAS concept.

The workshop features a stellar set of keynote speakers, and brings together a broad research community from academe, industry, labs, and government to discuss wide set of topics on challenges and opportunities, from fundamental research to efforts on comprehensive cyber-infrastructure environments, relating to DDDAS.

Co-sponsored by AFOSR and NSF, and other agencies participation, the workshop will expand on precedent research and programmatic activities, and emerging directions. A report, summarizing the workshop presentations and discussions, will be produced and made broadly available.

Workshop Co-Chairs

• Prof. Craig Douglas, University of Wyoming
• Prof. Abani Patra, University of Buffalo

Cross-Agencies Committee

DoD/AFOSR

• Dir. Frederica Darema
• Dr. Bob Bonneau
• Dr. Fariba Fahroo
• Dr. David Stargel
• Dr. Kitt Reinhardt

NSF

• Dr. Lee Jameson (MPS)
• Dr. Ed Seidel (MPS)
• Dr. Manish Parashar (OCI)
• Dr. George Maracas (ENG)
• Dr. Tom Henderson (CISE)
• Dr. John Cherniavsky (EHR)

DoD/DTRA

• Dr. Kiki Ikossi

DoD/ONR

• Dr.Ralph Wachter

DoD/ARL/CIS

• Dr. Ananthram Swarmi

NIH

• Dr. Milt Corn (NLM)
• Dr. Peter Lyster (NIGMS)

NASA

• Dr. Michael Seablom

Presentation Slides

Preliminary Talks

• Dr. Dahm, U.S. Air Force "Technology Horizons"
      Talk
• Dr. Ed Seidel, Data- and Compute-Driven Transformation of Science
      Talk
• Dr. Frederica Darema, InfoSymbioticSystems - The Power of: Dynamic Data-Driven Application Systems (DDDAS)
      Talk
• Prof. Abani Patra, AFOSR/NSF DDDAS Workshop Keystones
      Talk

Plenary Talks

• Prof. J. Tinsley Oden, A Dynamic Data-Driven System for Optimized Laser Treatment of Prostate Cancer
      Talk
• Prof. Kelvin Droegemeir, DDDAS Applied to High-Impact Local Weather: The LEAD Project
      Talk
• Prof. Charbal Farhat and Dr. John Michopoulos, DDDAS for Material Characterization, Health Monitoring, and Critical Event Prediction of Complex Structures
• Prof. George Karniadakis, Predictability and Uncertainty in DDDAS
      Talk
• Prof. Santae Kim, Is Life a Dynamic Data Driven DNA Application System?
      Talk
• Prof. Patrick Jaillet, Data-Driven Optimization: Illustrations, Opportunities, Some Results, Key Challenges
      Talk

Secondary Talk

• Prof. J. Tinsley Oden, A Brief View of Verification, Validation, and Uncertainty Quantification
      Talk

Working Group Charges

All WGs - Common and Overarching Issues (Craig Douglas and Abani Patra)

All WGs should address the following common and overarching issues:

• The scope of research challenges is clearly wide and in need of fundamental advances. Why is now the right time for fostering this kind of research?
• What are the Grand S&T Challenges in enabling DDDAS? What are ongoing research advances can be used as leverage and springboard to enable DDDAS?

(Each WG will address the research challenges and opportunities)

• What kinds of processes, venues and mechanisms are optimal to facilitate the multidisciplinary nature of the research needed in enabling such capabilities?
• What past or existing initiatives can contribute, and what new ones should be created to systematically support such efforts?
• What are the benefits of coordination and joint efforts across agencies, nationally and in supporting synergistically such efforts?
• What kinds of connections with the industrial sector can be beneficial? How can these be fostered effectively to focus research efforts and expedite technology transfer?
• How these new research directions can be used to create exciting new opportunities for undergraduate, graduate and postdoctoral education and training?
• What novel and competitive workforce development opportunities can ensue?
• What National and International critical challenges are addressed through DDDAS capabilities?

WG1 - Algorithms and Data Assimilation (George Biros and Janice Coen)

DDDAS environments require algorithms, mathematical and statistical, both numeric and non-numeric, that have good convergence properties under perturbations from streamed data into the executing application. DDDAS goes beyond the traditional data-assimilation approaches:

• What is the state-of-the-art and what are the challenges in the applications algorithms to enable such capabilities for the applications models/simulations?
• What algorithms? development is needed to enable application algorithms tolerant to perturbations from "on-line" input data, and with good stability properties?
• How can one select and incorporate dynamically appropriate algorithms as the application requirements and data sets change in the course of the simulation?
• What kinds of approaches, such as knowledge-based systems, can be employed, and what interfaces and applications assists are needed to allow such capabilities?
• What systems support is required to develop such environments?
• How do the existing methods and capabilities in the above need to be advanced?

WG2 - Uncertainty Quantification and MultiScale Modeling (Bani Mallick and Dongbin Xiu)

DDDAS environments entail application models that can interface and dynamically interact with the measurement data systems (archival, real-time data acquisition and control systems). Such interaction entails dynamic application models and application components, at runtime, as dictated by the streamed data, and can include dynamic invocation of models at multiple scales? that is "dynamic multi-scale". Models, experiments and observations are all representations and discrete samples of behavior. Quantifying and managing the outcomes of application systems (predictions, control actions, ?) must account for these uncertainties. Such situations ensue new and increased challenges, beyond the traditional multi-scale, and uncertainty quantification considerations.

• What are the overall opportunities and challenges in DDDAS applications modeling?
• What research and technologies are covered by the present projects?
• As DDDAS requirements are expected to be dynamic, what are the implied applications modeling technology advances that are need and what?s the needed systems support?
• What is special if you have a multiscale/multiphysics system? How do you do deal with multimodal data?
• What methodologies from the emerging field of UQ are applicable here, and in particular in the case where models of other components of the application are dynamically invoked? Conversely what new developments are needed to enable the use of dynamic data and simulations especially for complex systems? What are the issues in data management, dynamic selection of application components, mapping, interfaces for request and allocation of systems resources so that quality of service is ensured for the applications?
• Provide applications examples that will benefit from the new paradigm, existing and potential new applications, challenges in developing such applications, multilevel and multimodal modeling, composition of such complex applications, data management and interfaces to experiments/field-data, computation, memory and I/O requirements.

WG3 - Large and Heterogeneous Data from Distributed Measurement & Control Systems (Alok Chaturvedi and Adrian Sandhu)

DDDAS inherently involves large amounts of data that can result from heterogeneous and distributed sources, collected in differing time-scales and in different formats, and which need to be preprocessed before automatically integrating them to the executing applications that need use the new data.

• What is the state of the art in measurement systems and how are they integrated in DDDAS, where measurements from sensors, other instruments and data repositories are dynamically integrated with the application modeling to improve the application modeling?
• Conversely, what is the state of the art in on-line application control of the measurement instrument or process providing opportunity to improve the measurement process, guide the design and operational aspects of measurement instruments, and networks of distributed heterogeneous sensors and networks of embedded controllers?
• What are the methods that need to be developed to guide the architecture of sets of sensors and other instruments thus improving the effectiveness or efficiency of the measuring systems, and networks of distributed heterogeneous sensors and networks of embedded controllers?
• What are the challenges and opportunities in software and hardware technologies to enable such dynamic interfaces to such measurement and control systems, and their associated data sets? What improvements in the methods are expected, how are they going to be enabled?
• How the existing methods and capabilities in all the above need to be advanced?

WG4 - Building an Infrastructure for DDDAS (Gabrielle Allen and Shantenu Jha)

DDDAS integrates real-time sensor and other measurement devices with special purpose data processing systems together with the parts of the application that execute in larger platforms and driving a seamless integration of stationary and mobile devices together with large high-end platforms, entailing grids that go beyond the present computational grids.

• What are the challenges in the infrastructure just described above?
• What are the challenges and opportunities in software and hardware technologies to enable such dynamic interfaces?
• What improvements in the measurement methods are expected and how are they going to be enabled?

WG5 - Systems Software (Srinidhi Varadarajan and Dinesh Mamocha)

Quality of service, program software environments, data massaging, network security, and availability of common libraries are all important to making a DDDAS work in a global manner.

• What is the state-of-the-art and what advances are needed in algorithms and software and what new capabilities need to be provided by the underlying systems and platforms on which these applications execute, so that quality of service is ensured?
• What are the software challenges in the programming environments for the development and runtime support, under conditions where the underlying resources as well as the applications requirements might be changing at execution time?
• What are the issues in data management, dynamic selection of components, dynamic invocation of components, mapping to underlying resources, interfaces for request, and allocation of systems resources so that quality of service is ensured for the applications?
• What are the additional capabilities that are needed in the application support and systems management services?
• How can these be fostered effectively to focus research efforts and expedite technology transfer?

Detailed Agenda

All Plenary Sessions will take place at the Arlington Hilton (950 N. Stafford St.), Mezzanine Level.

Day 1, Monday, August 30, 2010

Day 2, Tuesday, August 31, 2010

Day 3, Wednesday, September 1, 2010

Initial Write-up of the Report by the Working Group Chairs and Organizers.